Incidental pulmonary embolism in patients with cancer : prevalence, underdiagnosis and evaluation of an AI algorithm for automatic detection of pulmonary embolism
(2023) In European Radiology 33. p.1185-1193- Abstract
Objectives: To assess the prevalence of reported and unreported incidental pulmonary embolism (iPE) in patients with cancer, and to evaluate an artificial intelligence (AI) algorithm for automatic detection of iPE. Methods: Retrospective cohort study on patients with cancer with an elective CT study including the chest between 2018-07-01 and 2019-06-30. All study reports and images were reviewed to identify reported and unreported iPE and were processed by the AI algorithm. Results: One thousand sixty-nine patients (1892 studies) were included. Per study, iPE was present in 75 studies (4.0%), of which 16 (21.3%) were reported. Unreported iPE had a significantly lower number of involved vessels compared to reported iPE, with a median of... (More)
Objectives: To assess the prevalence of reported and unreported incidental pulmonary embolism (iPE) in patients with cancer, and to evaluate an artificial intelligence (AI) algorithm for automatic detection of iPE. Methods: Retrospective cohort study on patients with cancer with an elective CT study including the chest between 2018-07-01 and 2019-06-30. All study reports and images were reviewed to identify reported and unreported iPE and were processed by the AI algorithm. Results: One thousand sixty-nine patients (1892 studies) were included. Per study, iPE was present in 75 studies (4.0%), of which 16 (21.3%) were reported. Unreported iPE had a significantly lower number of involved vessels compared to reported iPE, with a median of 2 (interquartile range, IQR, 1–4) versus 5 (IQR 3–9.75), p < 0.001. There were no significant differences in age, cancer type, or attenuation of the main pulmonary artery. The AI algorithm correctly identified 68 of 75 iPE, with 3 false positives (sensitivity 90.7%, specificity 99.8%, PPV 95.6%, NPV 99.6%). False negatives occurred in cases with 1–3 involved vessels. Of the unreported iPE, 32/59 (54.2%) were proximal to the subsegmental arteries. Conclusion: In patients with cancer, the prevalence of iPE was 4.0%, of which only 21% were reported. Greater than 50% of unreported iPE were proximal to the subsegmental arteries. The AI algorithm had a very high sensitivity and specificity with only three false positives, with the potential to increase the detection rate of iPE. Key Points: • In a retrospective single-center study on patients with cancer, unreported iPE were common, with the majority lying proximal to the subsegmental arteries. • The evaluated AI algorithm had a very high sensitivity and specificity, so has the potential to increase the detection rate of iPE.
(Less)
- author
- Wiklund, Peder ; Medson, Koshiar and Elf, Johan LU
- organization
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Artificial intelligence, Neoplasms, Pulmonary embolism, Retrospective studies, Venous thromboembolism
- in
- European Radiology
- volume
- 33
- pages
- 1185 - 1193
- publisher
- Springer
- external identifiers
-
- scopus:85136584417
- pmid:36002759
- ISSN
- 0938-7994
- DOI
- 10.1007/s00330-022-09071-0
- language
- English
- LU publication?
- yes
- id
- 7315b52a-041f-4f16-bab0-14e2ef21ab8a
- date added to LUP
- 2022-10-18 09:28:00
- date last changed
- 2024-07-25 18:50:23
@article{7315b52a-041f-4f16-bab0-14e2ef21ab8a,
abstract = {{<p>Objectives: To assess the prevalence of reported and unreported incidental pulmonary embolism (iPE) in patients with cancer, and to evaluate an artificial intelligence (AI) algorithm for automatic detection of iPE. Methods: Retrospective cohort study on patients with cancer with an elective CT study including the chest between 2018-07-01 and 2019-06-30. All study reports and images were reviewed to identify reported and unreported iPE and were processed by the AI algorithm. Results: One thousand sixty-nine patients (1892 studies) were included. Per study, iPE was present in 75 studies (4.0%), of which 16 (21.3%) were reported. Unreported iPE had a significantly lower number of involved vessels compared to reported iPE, with a median of 2 (interquartile range, IQR, 1–4) versus 5 (IQR 3–9.75), p < 0.001. There were no significant differences in age, cancer type, or attenuation of the main pulmonary artery. The AI algorithm correctly identified 68 of 75 iPE, with 3 false positives (sensitivity 90.7%, specificity 99.8%, PPV 95.6%, NPV 99.6%). False negatives occurred in cases with 1–3 involved vessels. Of the unreported iPE, 32/59 (54.2%) were proximal to the subsegmental arteries. Conclusion: In patients with cancer, the prevalence of iPE was 4.0%, of which only 21% were reported. Greater than 50% of unreported iPE were proximal to the subsegmental arteries. The AI algorithm had a very high sensitivity and specificity with only three false positives, with the potential to increase the detection rate of iPE. Key Points: • In a retrospective single-center study on patients with cancer, unreported iPE were common, with the majority lying proximal to the subsegmental arteries. • The evaluated AI algorithm had a very high sensitivity and specificity, so has the potential to increase the detection rate of iPE.</p>}},
author = {{Wiklund, Peder and Medson, Koshiar and Elf, Johan}},
issn = {{0938-7994}},
keywords = {{Artificial intelligence; Neoplasms; Pulmonary embolism; Retrospective studies; Venous thromboembolism}},
language = {{eng}},
pages = {{1185--1193}},
publisher = {{Springer}},
series = {{European Radiology}},
title = {{Incidental pulmonary embolism in patients with cancer : prevalence, underdiagnosis and evaluation of an AI algorithm for automatic detection of pulmonary embolism}},
url = {{http://dx.doi.org/10.1007/s00330-022-09071-0}},
doi = {{10.1007/s00330-022-09071-0}},
volume = {{33}},
year = {{2023}},
}